Volume-14 Issue-6, May 2025 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

F109614060525

IJITEE Journal — Sat, 10 May 2025 05:18:37 +0000

The International Journal of Innovative Technology and Exploring Engineering (IJITEE) has ISSN: 2278-3075 (online), an open-access, peer-reviewed, periodical monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, February, March, April, May, June, July, August, September, October, November and December.The journal aims to publish high–quality peer–reviewed original articles in the area of Engineering and Technology that covers Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering and all interdisciplinary streams of Engineering and Technology. #Smart Computing and Information Processing #Signal and Speech Processing #Image Processing and Pattern Recognition #WSN#Artificial Intelligence and machine learning #Data mining and warehousing #Data Analytics #Deep learning #Bioinformatics #High Performance computing #Advanced Computer Networking #Cloud Computing #IoT #Parallel Computing on GPU #Human Computer Interactions #Recent Trends in Microelectronics and VLSI Design #Process & Device Technologies #Low-Power Design #Nanometer-Scale Integrated Circuits #Application specific ICs (ASICs) #FPGAs #Nanotechnology #Nano Electronics and Quantum Computing #3. Challenges of Industry and their Solutions, Communications #Advanced Manufacturing Technologies #Artificial Intelligence #Autonomous Robots #Augmented Reality #Big Data Analytics and Business Intelligence #Cyber Physical Systems (CPS) #Digital Clone or Simulation #Industrial Internet of Things (IIoT) #Manufacturing IoT #Plant Cyber Security #Smart Solutions – Wearable Sensors and Smart Glasses #System Integration #Small Batch Manufacturing #Visual Analytics #Virtual Reality #3D Printing # Internet of Things (IoT) #Internet of Things (IoT) & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Block Chain-enabled IoT Device and Data Security and Privacy #Application of WSN in IoT #Cloud Resources Utilization in IoT #Wireless Access Technologies for IoT #Mobile Applications and Services for IoT #Machine/ Deep Learning with IoT & IoE #Smart Sensors and Internet of Things for Smart City #Logic, Functional programming and Microcontrollers for IoT #Sensor Networks, Actuators for Internet of Things #Data Visualization using IoT #IoT Application and Communication Protocol #Big Data Analytics for Social Networking using IoT #IoT Applications for Smart Cities #Emulation and Simulation Methodologies for IoT #IoT Applied for Digital Contents #Microwaves and Photonics #Microwave filter #Micro Strip antenna #Microwave Link design #Microwave oscillator #Frequency selective surface #Microwave Antenna #Microwave Photonics #Radio over Fibre #Optical Communication, #Optical Oscillator #Optical Link Design #Optical Phase Lock Loop #Optical Devices #Computation Intelligence and Analytics #Soft Computing #Advance Ubiquitous Computing #Parallel Computing #Distributed Computing #Machine Learning #Information Retrieval #Expert Systems #Data Mining #Text Mining #Data Warehousing #Predictive Analysis #Data Management #Big Data Analytics #Big Data Security #Energy Harvesting and Wireless Power Transmission #Energy Harvesting and Transfer for Wireless Sensor Networks #Economics of Energy Harvesting Communications #Waveform Optimization for Wireless Power Transfer #RF Energy Harvesting #Wireless Power Transmission #Microstrip Antenna Design and Application #Wearable Textile Antenna #Luminescence #Rectenna #Advance Concept of Networking and Database #Computer Network #Mobile Adhoc Network #Image Security #Application Artificial Intelligence and Machine Learning in the Field of Network and Database #Data Analytic #High Performance Computing #Pattern Recognition #Machine Learning (ML) and Knowledge Mining (KM) #Regression and Prediction #Problem Solving and Planning #Clustering #Classification #Neural Information Processing #Vision and Speech Perception #Heterogeneous and Streaming Data #Natural Language Processing #Probabilistic Models and Methods #Reasoning and inference #Marketing and Social Sciences #Data Mining #Knowledge Discovery #Web Mining #Information 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The Natural Language Processing Axioms in Classical Tamil for Zonal Dialects using Machine Learning
Perumal Sivarman¹, Prabaharan G², Senthil Kumar R³

¹Perumal Sivaraman, Department of Information Technology, UTAS – Nizwa, Oman (Nizwa), Oman.

²Dr. Prabaharan G, Department of Computer Science and Engineering, Vel Tech Rangarajan, Dr. Sagunthala R and D Institute of Science and Technology, Morai (Tamil Nadu), India.

³Dr. Senthil Kumar R, Department of Computer Science and Engineering, Jain Deemed University, Bengaluru (Karnataka), India.

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Studying Natural Language Processing (NLP) for Classical Tamil and its Zonal Dialects using Machine Learning (ML) involves unique challenges and opportunities. Classical Tamil, one of the oldest languages with a rich literary heritage, differs significantly in syntax, semantics, and phonetics from its modern dialects. Addressing these differences requires incorporating linguistic axioms and cultural nuances into NLP systems. This deals with Tamil letters, Challenges, Future directions, and Lexical Differences. It also includes parsers and tokenisation. Lists the differences between Morphemes, Bounded Morphemes in terms of Tamil as a Natural Language processing—dictionary form of the words used in Lemmatizations. Stemming reduces the words, and Tamil is represented as a short sentence, comparing the differences in the Tamil dialect taken and represented. The methodology used is Clustering algorithms, which can group zonal dialects based on phonetic and semantic similarities using a Naïve Bayes classifier. We are using speechto-text to identify the Tamil dialect. This zonal dialect is essential in entertainment, education, information, and business. More Exploration can be done using Zonal dialects in Classical Tamil. Machine learning plays a role in classification, Grouping, and Segmenting Natural Language processing. We have different dialects in the Single Language Tamil for a single word in Natural Language Processing. Encourages local people to communicate fluently in terms of transactions. Preserving local traditions and customs is one of the advantages of Zonal Dialects. It can be used in interviews, recordings, written and spoken texts, as well as debates. Linguistic Diversity, preservation of History, and cultural identity are significant concerns in Zonal dialects that use classical Tamil.

Keywords: (must be 3-5), Zonal Dialects, Machine Learning, Naïve Bayes.
Scope of the Article: Artificial Intelligence and Methods

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F109214060525

IJITEE Journal — Sat, 10 May 2025 05:00:04 +0000

Stabilization and Performance Analysis of an Inverted Pendulum using Classical and Intelligent Control Techniques
Shrutosom Mukherjee¹, Mrinal Buragohain²

¹Shrutosom Mukherjee, Department of Electrical Engineering, Jorhat Engineering College, Jorhat (Assam), India.

²Dr. Mrinal Buragohain, Professor, Department of Electrical Engineering, Jorhat Engineering College, Jorhat (Assam), India.

Abstract: The inverted pendulum system is a classical benchmark in control theory, known for its nonlinear and unstable dynamics. This paper presents a comparative study of three advanced control strategies: Linear Quadratic Regulator (LQR), Model Predictive Control (MPC), and Fuzzy Logic Control (FLC) for stabilizing an inverted pendulum system. Each controller is designed to stabilise the pendulum upright while minimising cart displacement. Performance is evaluated based on settling time, rise time, steady-state error, and control effort under nominal and perturbed conditions, including varying pendulum mass and initial angle. Results indicate that while LQR offers a fast response, it demands high control energy. MPC ensures precise tracking but is computationally intensive. FLC provides a robust and energy-efficient balance, making it ideal for uncertain environments.

Keywords: Control Effort, Fuzzy Logic Control, Inverted Pendulum, LQR, MPC, Robustness.
Scope of the Article: Control and Automation

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E108314050425

IJITEE Journal — Thu, 01 May 2025 09:55:05 +0000

Development and Implementation of a Custom License Plate Detection and Recognition System Using YOLOv10 and Tesseract OCR: A Comprehensive Study in Computer Vision and Optical Character Recognition Technologies
Priyankush Kaushik Baruah¹, Pranabjyoti Haloi²

¹Priyankush Kaushik Baruah, Department of Electrical Engineering, Jorhat Engineering College, Jorhat (Assam), India.

²Dr. Pranabjyoti Haloi, Associate Professor, Department of Electrical Engineering, Jorhat Engineering College, Jorhat (Assam), India.

Abstract: This study presents an automated license plate detection and recognition system that combines YOLOv10 for realtime object detection and Tesseract OCR for robust text extraction. The methodology involves training a customised YOLOv10 model on annotated vehicle datasets to localize license plates, followed by region-of-interest (ROI) filtering to enhance accuracy. Detected plates are processed with Tesseract OCR to convert visual data into machine-readable text. Evaluated using precision, recall, and inference speed metrics, the system achieves 97% detection accuracy and real-time performance, demonstrating reliability in automated vehicle identification tasks such as traffic monitoring. This work highlights the synergy between YOLOv10’s detection efficiency and Tesseract’s OCR capabilities, providing a scalable solution for intelligent transportation systems.

Keywords: License Plate Recognition (LPR), YOLOv10, Optical Character Recognition (OCR), Object Detection, Intelligent Transportation Systems (ITS), Real-Time Monitoring.
Scope of the Article: Computer Vision

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IJITEE Journal — Thu, 01 May 2025 09:41:33 +0000

TC-Trissea (Tuguegarao City Tricycle Riders Information, Security and Satisfaction Enhancement App): A Proposed Mobile App for Tricycle Commuters of Tuguegarao City
Jesus B. Pizarro¹, Maria Visitacion N. Gumabay², Sheena G. Gumarang³

¹Dr. Jesus B. Pizarro, Department of Mathematics and Public Administration, St. Paul University Philippines, Tuguegarao City (Cagayan), Philippines.

²Dr. Maria Visitacion N. Gumabay, Department of Information Technology, St. Paul University Philippines, Tuguegarao City (Cagayan), Philippines.

³Dr. Sheena G. Gumarang, Department of Information Technology, St. Paul University Philippines, Tuguegarao City (Cagayan), Philippines.

Abstract: The tricycle transportation system in Tuguegarao City in Northern Philippines is perennially confronted with problems and challenges that have to do with the tricycle commuters’ safety, the quality of service that they receive from drivers and their deteriorating overall level of satisfaction as commuters. To address these issues, the Tuguegarao City Tricycle Riders Information, Security, and Satisfaction Enhancement App (TC-TRISSEA) was developed as a mobile application to enhance the commuters’ experiences by integrating technological innovations in the app’s interface. The study employed an exploratory sequential mixedmethods research design. Qualitative data were gathered through formal interviews with tricycle commuters and drivers to identify issues and concerns that served as the basis for developing the survey instruments. In the quantitative phase of the study, 90 participants were surveyed and assessed the mobile app’s net effect on commuters’ safety, satisfaction, and usability. The Technology Acceptance Model (TAM) served as the foundation for the quantitative phase of the study. Ten IT experts served as evaluators to measure the app’s compliance with ISO 25010 software quality standards. Findings revealed that consumers consistently expressed dissatisfaction with the current tricycle system, particularly regarding safety, fare payment, and the professionalism and behaviour of tricycle drivers. The developed TC-TRISSEA app addressed these concerns through embedded features, including real-time tracking, a feedback mechanism, and driver profile verification using QR codes. The IT experts rated the app as compliant to a “Very Great Extent” with ISO 25010 software quality standards, thus confirming that it is robust and usable. The study revealed that the app significantly enhanced commuter safety and overall satisfaction by addressing the areas of inefficiencies and promoting accountability among drivers. The app’s adherence to international software quality standards underscores its potential as a scalable model for urban mobility solutions in cities and municipalities across the Philippines.

Keywords: Tricycle Transportation System, Mobile Application, Commuter Safety, Urban Mobility Solutions, ISO 25010 Software Standards.
Scope of the Article: Information Technology

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D107514040325

IJITEE Journal — Thu, 01 May 2025 09:34:20 +0000

Agile Methodology Integrated Programming Planned (PIP) to Optimize the Development of Educational Software
Cesar Patricio-Peralta¹, Jesús Zamora Mondragon², Jacker Paredes Meneses³, Jimmy Ramirez Villacorta⁴, Adan Eugenio Contreras Angeles⁵, Carlos Alberto Garcia Cortegano⁶

¹Cesar Patricio-Peralta, Universidad Nacional Federico Villarreal, Lima, Perú.

²Jesús Zamora Mondragon, Universidad César Vallejo, Lima, Perú.

³Jacker Paredes Meneses, Universidad Nacional de la Amazonia Peruana, Iquitos, Perú.

⁴Jimmy Max Ramirez Villacorta, Universidad Nacional de la Amazonia Peruana, Iquitos, Perú.

⁵Adan Eugenio Contreras Angeles, Universidad Tecnológica del Perú, Lima, Perú.

⁶Carlos Alberto Garcia Cortegano, Universidad Nacional de la Amazonia Peruana, Iquitos, Perú.

Abstract: The new Agile Methodology, Planned Integrated Programming (PIP), is an efficient and robust alternative for manufacturers, developers, and students of Software Engineering. The study employs an experimental design that enables the evaluation of the impact of the Agile PIP Methodology on the development of educational software. The population consisted of 5 professionals in charge of creating and maintaining Educational Software, 15 teachers and 10 students from the School of Systems Engineering of the University of San Martín de Porres. The Results: Based on chi-square tests, they demonstrate that PIP has a significant impact. With a Continuity Correction statistic value of 8.643 and a p-value of 0.003, it is concluded that PIP significantly improves the development of educational software, reducing development times, testing errors, and improving satisfaction. The application of PIP in the School of Systems Engineering at USMP proved effective, with an 80% effectiveness rate according to the scale indicators. Conclusions: The Agile Planned Integrated Programming (PIP) methodology has proven to be a valuable resource for developing educational software in the university context, achieving substantial improvements in quality, delivery times, and user satisfaction, which validates its application in other similar projects within the academic sector.

Keywords: Methodology, Agile, Flexibility, Adaptability, Educational Software, Planned Integrated Programming (PIP).
Scope of the Article: Software Engineering & Applications

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Volume-14 Issue-6, May 2025 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

F109614060525

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